New submission for PAS-19-391 (Small Research Grant Program for the Next Generation of Researchers in AD/ADRD Research: Area of Focus Archiving and Leveraging Existing Data Sets for Analyses [R03]). Recent statistics show that if everyone alive in 2018 who will develop Alzheimer?s disease (AD) had early and accurate diagnosis, there would be a savings of $7.9 trillion in medical and long-term care costs. Although the advent of Alzheimer?s disease (AD) biomarkers has revolutionized our understanding of AD pathogenesis during the preclinical phase, these approaches are often expensive, invasive, inaccessible due to rural location, cost, or medical contraindications. Additionally, beyond a focus on AD biomarkers alone, it is essential to emphasize that cognitive difficulties and subsequent functional impairment are the features of the disease that negatively impact the lives of patients and their families. Emerging evidence suggests that subtle cognitive changes may develop much earlier than originally described in models of AD and these subtle cognitive changes add meaningful prognostic value, above and beyond AD biomarkers, in predicting progression to mild cognitive impairment (MCI) and dementia. The gold standard approach for identifying subtle cognitive decline in preclinical AD, however, remains unclear. Therefore, we propose to apply four different classification algorithms for subtle cognitive decline in the open source Alzheimer?s Disease Neuroimaging Initiative (ADNI) dataset. The four classifications methods include two subjective approaches: self-reported subjective cognitive decline (Self-SCD) and informant-reported subjective cognitive decline (Inform-SCD); and two objective approaches: a sensitive neuropsychological individual test-based approach called objectively-defined subtle cognitive decline (Obj-SCD) and a composite score-based approach using the preclinical Alzheimer?s cognitive composite to identify subtle cognitive decline (PACC-SCD).
The specific aims of this proposal include: 1) Compare AD biomarkers across 4 subtle cognitive decline definitions (Self-SCD, Inform-SCD, Obj-SCD, and PACC-SCD); 2) Determine which subtle cognitive decline definitions best capture objective cognitive decline in the year preceding the subtle cognitive decline classification; and 3) Examine longitudinal a) clinical and b) biomarker progression across subtle cognitive decline definitions to determine the definitions with the best predictive utility. Results of the proposed aims will likely impact the design of future studies, as having simple, yet reliable, and highly cost- efficient methods for narrowing the initial pool of participants so that only those at greatest risk require a PET scan for screening purposes would result in significant cost-savings. Additionally, these results will serve as critical preliminary data for future grant applications, and be a key step toward improving clinically meaningful early detection methods of those at risk for future decline, particularly those with limited access to AD biomarker testing.
Early identification of individuals at risk for future progression to mild cognitive impairment and dementia is critical to engaging in early interventions that may slow, delay, or reduce the risk for future decline as well as for optimizing clinical trial recruitment. We seek to compare different methods of identifying subtle cognitive decline as they relate to Alzheimer?s disease biomarkers, recent rate of cognitive decline, and future progression to improve our understanding of each method?s precision and utility as an inexpensive and non-invasive tool for early detection. Determination of the best approach will likely have important impacts on prospective design of future studies and, ultimately, clinical care and prevention.
